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STUDY OBJECTIVE: We implemented a virtual observation unit in which emergency department (ED) patients receive observation-level care at home. Our primary aim was to compare this new care model to in-person observation care in terms of brick-and-mortar ED length of stay (inclusive of ED observation unit time) as well as secondarily on inpatient admission and 72-hour return visits (overall and with admission). METHODS: In a retrospective analysis of electronic health record data on ED observation patients from January 1, 2022 to December 29, 2022 from an academic urban ED, we used propensity matching to compare virtual to in-person observation patients on outcomes of interest. Patients were matched 1:1 based on age, sex, Charlson Comorbidity Index, and reason for observation. We also conducted real-time review of all virtual observation cases for potential safety concerns. RESULTS: Of 8,218 observation stays, 361 virtual observation patients were matched with 361 in-person observation patients. Virtual observation patients experienced lower median brick-and-mortar ED + EDOU LOS [14.6 (IQR 10.2, 18.9) versus 33.3 (IQR 28.1, 38.1) hours] and lower inpatient admission rates (10.2% [SD 5.0] versus 24.7% [SD 11.3]). The 72-hour return rate was higher for virtual observation patients (3.6% [SD 3.0] versus 2.5% [SD 3.0]). Among those with return visits, the rate of inpatient admission was higher among virtual observation patients (53.8% [SD 3.2] versus 11.1% [13.0]). There were no significant patient safety events recorded. CONCLUSION: Virtual observation unit patients used fewer hours in ED and ED observation relative to on-site observation patients. This new care delivery model warrants further study because it has the potential to positively impact ED capacity.
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INTRODUCTION: While emergency department (ED) crowding has myriad causes and negative downstream effects, applying systems engineering science and targeting throughput remains a potential solution to increase functional capacity. However, the most effective techniques for broad application in the ED remain unclear. We examined the hypothesis that Lean-based reorganization of Fast Track process flow would improve length of stay (LOS), percent of patients discharged within one hour, and room use, without added expense. METHODS: This study was a prospective, controlled, before-and-after analysis of Fast Track process improvements in a Level 1 tertiary care academic medical center with >95,000 annual patient visits. We included all adult patients seen during the study periods of 6/2010-10/2010 and 6/2011-10/2011, and data were collected from an electronic tracking system. We used concurrent patients seen in another care area used as a control group. The intervention consisted of a simple reorganization of patient flow through existing rooms, based in systems engineering science and modeling, including queuing theory, demand-capacity matching, and Lean methodologies. No modifications to staffing or physical space were made. Primary outcomes included LOS of discharged patients, percent of patients discharged within one hour, and time in exam room. We compared LOS and exam room time using Wilcoxon rank sum tests, and chi-square tests for percent of patients discharged within one hour. RESULTS: Following the intervention, median LOS among discharged patients was reduced by 15 minutes (158 to 143 min, 95%CI 12 to 19 min, p<0.0001). The number of patients discharged in <1 hr increased by 2.8% (from 6.9% to 9.7%, 95%CI 2.1% to 3.5%, p<0.0001), and median exam room time decreased by 34 minutes (90 to 56 min, 95%CI 31 to 38 min, p<0.0001). In comparison, the control group had no change in LOS (265 to 267 min) or proportion of patients discharged in <1 hr (2.9% to 2.9%), and an increase in exam room time (28 to 36 min, p<0.0001). CONCLUSION: In this single center trial, a focused Lean-based reorganization of patient flow improved Fast Track ED performance measures and capacity, without added expense. Broad multi-centered application of systems engineering science might further improve ED throughput and capacity.